greencredit dataset

greencredit Bayesian Network

The coupling relationships and influence mechanisms of green credit and energy-environment-economy under China's goal of carbon neutrality. data

Format

A discrete Bayesian network nvestigate the coupling relationships and influence mechanisms of green credit and 3E system. Probabilities were given within the referenced paper (missing distributions were set as uniform). The vertices are:

• ECS: Energy consumption structure (High, Medium, Low);
• EI: Energy intensity (High, Medium, Low);
• EPI: Environment (High, Medium, Low);
• GCI: Interest expense proportion (High, Medium, Low);
• GDP: Economy sharing (High, Medium, Low);
• IS: Green economy (High, Medium, Low);
• OU: Economy opening up (High, Medium, Low);
• PEC: Per capita energy consumption (High, Medium, Low);
• TP: Economy innovation (High, Medium, Low);
• UR: Economy coordination (High, Medium, Low);

Returns

An object of class bn.fit. Refer to the documentation of bnlearn for details.

References

Chai, J., Wang, Y., Hu, Y., Zhang, X., & Zhang, X. (2023). The Coupling Relationships and Influence Mechanisms of Green Credit and Energy-Environment-Economy Under China's Goal of Carbon Neutrality. Journal of Systems Science and Complexity, 36(1), 360-374.